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An IT industry analyst article published by SearchITOperations.

When everything from the coffee maker to the manufacturing plant’s robots to the electric grid is connected, shouldn’t security be IT’s primary concern?

Mike Matchett
Small World Big Data

I was recently asked about the most pressing IT challenge in 2018. At first, I was going to throw out a pat answer, something like dealing with big data or finally deploying hybrid cloud architecture. But those aren’t actually all that difficult to pull off anymore.

We should be much more afraid of today’s human ignorance than tomorrow’s AI.

Then I thought about how some people like to be irrationally scared about the future, and bogeyman like artificial intelligence in particular. But AI really isn’t the scary part. It’s the blind trust we already tend to put into black-box algorithms and short-sighted local optimizations that inevitably bring about unintended consequences. We should be much more afraid of today’s human ignorance than tomorrow’s AI.

Instead, what I came up with as the hard, impending problem for IT is how to adequately secure the fast-expanding internet of things. To be clear, I interpret IoT rather broadly to include existing mobile devices — e.g., smartphones that can measure us constantly with multiple sensors and GPS — connected consumer gadgets and household items, and the burgeoning realm of industrial IoT.

The rush to secure IoT devices isn’t just about your personal things, as in the risk of someone hacking your future driverless car. The potential scope of an IoT security compromise is, by definition, huge. Imagine every car on the road hacked — at the same time.

IoT exploits could also go wide and deep. Sophisticated compromises could attack your car, your phone, your home security system, your pacemaker and your coffeepot simultaneously. Imagine every coffee machine out of service on the same morning. We haven’t even begun to outline the potential nightmare scenarios caused by insecure IoT devices. And I sure hope Starbucks is keeping some analog percolators on standby.

If personal physical danger isn’t scary enough, think about the ease with which a single penetration of a key connected system could cause a nationwide or even global disaster. For example, a 2003 cascading power outage that affected over 50 million people in New England was triggered by a single alarm system misconfiguration. An inability to recover or reset something easily at that scale could push one into imagining a truly dystopian future.

Vulnerable with a capital V
What worries me more than the possibility of a large, direct attack is the very real likelihood of slow, insidious, creeping subversion, achieved through IoT device security breaches. And not just by one party or a single bad actor, but by many competing interests and organizations over time — some with supposedly good intentions.

We will make mistakes, take shortcuts and ignore vulnerabilities until it’s too late.

The total IoT attack surface will be too large to keep everything fully secured…(read the complete as-published article there)

An IT industry analyst article published by SearchITOperations.

Automation technologies create an artificial brain for IT operations, but that won’t turn skilled admins and engineers into zombies — far from it.

Mike Matchett
Small World Big Data

As a technology evangelist and professional IT systems optimizer, I see the benefits of IT automation and can only champion trends that increase it. When we automate onerous tasks and complex manual procedures, we naturally free up time to focus our energies higher in the stack. Better and more prevalent automation increases the relative return on our total effort so that we each become more productive and valuable. Simply put, IT automation provides leverage. So it’s all good, right?

Another IT automation benefit is that it captures, encapsulates and applies valuable knowledge to real-world problems. And actually, it’s increasingly hard to find IT automation platforms that don’t promote embedded machine learning and artificially intelligent algorithms. There is a fear that once our hard-earned knowledge is automated, we’ll no longer be necessary.

So, of course, I need to temper my automation enthusiasm. Automation can eliminate low-level jobs, and not everyone can instantly adjust or immediately convert to higher-value work. For example, industrial robots, self-driving cars or a plethora of internet of things (IoT)-enabled devices that cut out interactions with local retailers all tend to remove the bottom layer of the related pyramid of available jobs. In those situations, there will be fewer, more-utilized positions left as one climbs upward in skill sets.

Still, I believe automation, in the long run, can’t help but create even more pyramids to climb. We are a creative species after all. Today, we see niches emerging for skilled folks with a combination of internal IT and, for example, service provider, high-performance computing, data science, IoT and DevOps capabilities.

Automation initiatives aren’t automatic

If one squints a bit, almost every IT initiative aims to increase automation.

A service provider has a profit motive, so the benefit of IT automation is creating economies of scale. Those, in turn, drive competitive margins. But even within enterprise IT, where IT is still booked as a cost center, the drive toward intelligent automation is inevitable. Today, enterprise IT shops, following in the footsteps of the big service providers, are edging toward hybrid cloud-scale operations internally and finding that serious automation isn’t a nice-to-have, but a must-have.If one squints a bit, almost every IT initiative aims to increase automation. Most projects can be sorted roughly into these three areas with different IT automation benefits, from cost savings to higher uptime:

An IT industry analyst article published by SearchDataCenter.

Emerging technologies such as containers, HCI and big data have blurred the lines between compute and storage platforms, breaking down traditional IT silos.

Mike Matchett

With the rise of software-defined storage, in which storage services are implemented as a software layer, the whole idea of data storage is being re-imagined. And with the resulting increase in the convergence of compute with storage, the difference between a storage platform and a data-processing platform is further eroding.

Storage takes new forms

Let’s look at a few of the ways that storage is driving into new territory:

Now in containers! Almost all new storage operating systems, at least under the hood, are being written as containerized applications. In fact, we’ve heard rumors that some traditional storage systems are being converted to containerized form. This has a couple of important implications, including the ability to better handle massive scale-out, increased availability, cloud-deployment friendliness and easier support for converging computation within the storage.

Merged and converged. Hyper-convergence bakes software-defined storage into convenient, modular appliance units of infrastructure. Hyper-converged infrastructure products, such as those from Hewlett Packard Enterprise’s SimpliVity and Nutanix, can greatly reduce storage overhead and help build hybrid clouds. We also see innovative approaches merging storage and compute in new ways, using server-side flash (e.g., Datrium), rack-scale infrastructure pooling (e.g., Drivescale) or even integrating ARM processors on each disk drive (e.g., Igneous).

Bigger is better. If the rise of big data has taught us anything, it’s that keeping more data around is a prerequisite for having the opportunity to mine value from that data. Big data distributions today combine Hadoop and Spark ecosystems, various flavors of databases and scale-out system management into increasingly general-purpose data-processing platforms, all powered by underlying big data storage tools (e.g., Hadoop Distributed File System, Kudu, Alluxio).

Always faster. If big is good, big and fast are even better. We are seeing new kinds of automatically tiered and cached big data storage and data access layer products designed around creating integrated data pipelines. Many of these tools are really converged big data platforms built for analyzing big and streaming data at internet of things (IoT) scales.

The changing fundamentals

Powering many of these examples are interesting shifts in underlying technical capabilities. New data processing platforms are handling more metadata per unit of data than ever before. More metadata leads to new, highly efficient ways to innovate …(read the complete as-published article there)

An IT industry analyst article published by SearchITOperations.

Securing IoT data should become a priority as more companies manipulate the volumes produced by these devices. Seemingly innocuous information could allow privacy invasions.

Mike Matchett

The data privacy and access discussion gets all the more complicated in the age of IoT.

Some organizations might soon suffer from data paucity — getting locked, outbid or otherwise shut out of critical new data sources that could help optimize future business. While I believe that every data-driven organization should start planning today to avoid ending up data poor, this concern is just one of many potential data-related problems arising in our new big data, streaming, internet of things (IoT) world. In fact, issues with getting the right data will become so critical that I predict a new strategic data enablement discipline will emerge to not just manage and protect valuable data, but to ensure access to all the necessary — and valid — data the corporation might need to remain competitive.

In addition to avoiding debilitating data paucity, data enablement will mean IT will also need to consider how to manage and address key issues in internet of things data security, privacy and veracity. Deep discussions about the proper use of data in this era of analytics are filling books, and much remains undetermined. But IT needs to prepare for whatever data policies emerge in the next few years.

Piracy or privacy?

Many folks explore data privacy in depth, and I certainly don’t have immediate advice on how to best balance the personal, organizational or social benefits of data sharing, or where to draw a hard line on public versus private data. But if we look at privacy from the perspective of most organizations, the first requirements are to meet data security demands, specifically the regulatory and compliance laws defining the control of personal data. These would include medical history, salary and other HR data. Many commercial organizations, however, reserve the right to access, manage, use and share anything that winds up in their systems unless specifically protected — including any data stored or created by or about their employees.

If you are in the shipping business, using GPS and other sensor data from packages and trucks seems like fair game. After all, truck drivers know their employers are monitoring their progress and driving habits. But what happens when organizations track our interactions with IoT devices? Privacy concerns arise, and the threat of an internet of things security breach looms.

Many people are working hard to make GPS work within buildings, ostensibly as a public service, using Wi-Fi equipment and other devices to help triangulate the position of handheld devices and thus locate people in real time, all the time, on detailed blueprints.

In a shopping mall, this tracking detail would enable directed advertising and timely deals related to the store a shopper enters. Such data in a business setting could tell your employer who is next to whom and for how long, what you are looking at online, what calls you receive and so on. Should our casual friendships — not to mention casual flirting — bathroom breaks and vending machine selections be monitored this way? Yet the business can make the case that it should be able to analyze those associations in the event of a security breach — or adjust health plan rates if you have that candy bar. And once that data exists, it can be leaked or stolen…(read the complete as-published article there)

Today at #snyc18 learning about the latest in #serverless. Opportunity is huge (iRobot is 100% serverless and loving it @ben11kehoe ), but not a panacea, lots of work to do to build up full production applications yet according to Kelsey Hightower (google) @kelseyhightower .